Supervised Classification

The automatic interpretation of noun-noun compounds is an important subproblem within many natural language processing applications and is an area of increasing interest. The problem is difficult, with dis- agreement …...

Despite its substantial coverage, Nom- Bank does not account for all within- sentence arguments and ignores extra- sentential arguments altogether. These ar- guments, which we call implicit, are im- portant …...

In this paper, we systematically assess the value of using web-scale N-gram data in state-of-the-art supervised NLP classifiers. We compare classifiers that include or ex- clude features for the counts …...

. This paper deals with the description and the automatic tracking of text segments containing obsolescence in encyclopedia texts. We assume that despite the non-linguistic nature of this phenomenon, discursive …...

We present a first known result of high pre- cision rare word bilingual extraction from comparable corpora, using aligned compara- ble documents and supervised classification. We incorporate two features, a …...

We describe a set of experiments using au- tomatically labelled data to train supervised classifiers for multi-class emotion detection in Twitter messages with no manual inter- vention. By cross-validating between …...

Learning inference relations between verbs is at the heart of many semantic applications. However, most prior work on learning such rules focused on a rather narrow set of in- formation …...

This paper investigates the problem of automated text aesthetics prediction. The avail- ability of user generated content and ratings, e.g. Flickr, has induced research in aesthet- ics prediction for non-text …...

In this paper we introduce our system ca- pable of producing semantic parses of sen- tences using three different annotation for- mats. The system was used to partic- ipate in …...

AbstractThe automated comparison of points of view between two politicians is a very challenging task, due not only to the lack of annotated resources, but also to the different dimensions …...

AbstractSpoken conversation corpora often adapt existing Dialogue Act (DA) annotation specifications, such as DAMSL, DIT++, etc., to task specific needs, yielding incompatible annotations; thus, limiting corpora re-usability. Recently accepted ISO …...

AbstractSocial media collect and spread on the Web personal opinions, facts, fake news and all kind of information users may be interested in. Applying argument mining methods to such heterogeneous …...

AbstractUnknown words are a challenge for any NLP task, including sentiment analysis. Here, we evaluate the extent to which sentiment polarity of complex words can be predicted based on their …...

AbstractThis paper describes our system participation in the SemEval-2017 Task 8 ‘RumourEval: Determining rumour veracity and support for rumours’. The objective of this task was to predict the stance and …...

AbstractThis paper describes our contribution to the SemEval-2019 Task 5 on the detection of hate speech against immigrants and women in Twitter (hatEval). We considered a supervised classification-based approach to …...

AbstractTo detect how and when readers are experiencing engagement with a literary work, we bring together empirical literary studies and language technology via focusing on the affective state of absorption. …...

AbstractThis paper studies event causality identification, which aims at predicting the causality relation for a pair of events in a sentence. Regarding event causality identification as a supervised classification task, …...

AbstractWhile the field of argument mining has grown notably in the last decade, research on the Twitter medium remains relatively understudied. Given the difficulty of mining arguments in tweets, recent …...

AbstractThe concerning rise of hateful content on online platforms has increased the attention towards automatic hate speech detection, commonly formulated as a supervised classification task. State-of-the-art deep learning-based approaches usually …...